title: Model-based iterative reconstruction: effect on patient radiation dose and image quality in pediatric body CT.
abstract: OBJECTIVE
  To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection.
  
  
  METHODS
  Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDI(vol)) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis.
  
  
  RESULTS
  In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDI(vol) was 46% (range, 19%-65%) and mean decrease in SSDE was 44% (range, 19%-64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR.
  
  
  CONCLUSIONS
  CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality.
authors.affiliation: From the Section of Pediatric Radiology, Department of Radiology, C.S. Mott Children's Hospital-University of Michigan Health System, 1540 E Hospital Dr, SPC 4252, Ann Arbor, MI 48109-4252 (E.A.S., J.R.D., P.J.S.); Department of Radiology, University of Michigan Health System, Ann Arbor, Mich (M.M.G., E.G.C.); and Department of Biostatistics, Michigan Institute for Clinical and Health Research, Ann Arbor, Mich (N.K.).
authors.forename: Ethan A
authors.initials: EA
authors.lastname: Smith
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Dillman
authors.forename: Mitchell M
authors.initials: MM
authors.lastname: Goodsitt
authors.forename: Emmanuel G
authors.initials: EG
authors.lastname: Christodoulou
authors.forename: Nahid
authors.initials: N
authors.lastname: Keshavarzi
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Strouse
mesh_terms: D000293:Adolescent; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D006801:Humans; D007223:Infant; D009369:Neoplasms / Q000000981:diagnostic imaging*; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted; D011860:Radiography, Abdominal; D013902:Radiography, Thoracic; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055815:Young Adult